A beam-space method for Direction of Arrival and power estimation by exploiting the sparsity

In this paper, we propose a beam-space Sparse Spectral Fitting method (BMSpSF) for Directions-Of-Arrival (DOA) and power estimation. In order to reduce the computational complexity of sparsity methods and improve the selection of the regularization parameter, a beam-space technique is used to Sparse Spectral Fitting method. Firstly, we use the beamforming matrix to transfer element-space data to beam-space. Then, the output covariance matrix of beam-space domain will replace the original covariance matrix. Finally, we estimate the DOA and power by exploiting a sparse representation of the power spectrum. Simulation examples are presented to demonstrate the effective of the proposed method. The beam-space method not only remains the performances of DOA and power estimation of SpSF, but also is much less sensitive to its regularization parameter than that of the element-space SpSF.